machine learning – The productivity of Colab: to load directly from the Net(e.g. Kaggle) databases or to upload them on the colab directory and then extract them?

Recently I tried to search for the fastest approach to work with large data files in colab. Because I use colab as an environment for machine learning and thus have used files from the physical hard drive on the computer. However, I began to wonder if it would be better to upload them directly from the site (e.g. Kaggle), or to upload them onto the colab own directory and work with them from there. I was able to do the latter, but when the files began to unzip, the system suddenly stopped working and crashed. I tried again, and next time I waited longer until everything was unzipped. However, on the second step the system crashed again.

What I am asking here is the following:
Because my laptop is not very new, and I would like to use the colab environment as a tool for working with the ML outside of my own PC, would you suggest the best way to work with (large) databases without crashing of the system.

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